Deep Learning (Record no. 46519)

MARC details
000 -LEADER
fixed length control field 02146nam a22001817a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251125092148.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9780262537551
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Author Mark KEL-D
100 ## - MAIN ENTRY--AUTHOR
Author Name Kelleher, John D.
245 ## - TITLE STATEMENT
Title Deep Learning
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of Publication USA
Name of publisher, distributor, etc. The MIT Press
Date of publication, distribution, etc. 2019
300 ## - PHYSICAL DESCRIPTION
Pages X, 280 p.
490 ## - SERIES STATEMENT
Series Statement The MIT Press Essential Knowledge series
500 ## - GENERAL NOTE
General note An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars.<br/>Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.<br/><br/>Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning—major trends, possible developments, and significant challenges.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Subject / Department Artificial Intelligence
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection code Permanent Location Current Location Shelving Location Date acquired Source of acquisition Price Inventory number Total Checkouts Full Call Number Accession No./Barcode Date last seen Koha item type
        Computer Science Air University Kharian Campus Library Air University Kharian Campus Library Artificial Intelligence 11/06/2025 Ali Book Service 1682.00 ref.KMA/10536   006.3 KEL-D AUKHP0465 11/25/2025 Book
        Computer Science Air University Kharian Campus Library Air University Kharian Campus Library Artificial Intelligence 11/06/2025 Ali Book Service 1682.00 ref.KMA/10536   006.3 KEL-D AUKHP0466 11/25/2025 Book
        Computer Science Air University Kharian Campus Library Air University Kharian Campus Library Artificial Intelligence 11/06/2025 Ali Book Service 1682.00 ref.KMA/10536   006.3 KEL-D AUKHP0467 11/25/2025 Book
        Computer Science Air University Kharian Campus Library Air University Kharian Campus Library Artificial Intelligence 11/06/2025 Ali Book Service 1682.00 ref.KMA/10536   006.3 KEL-D AUKHP0468 11/25/2025 Book
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